This chapter outlines the differences between applications and database based systems. It discusses basics regarding database structure and design theory. Application based approach to Event Processing (Define Here): Application based approach focuses on the process that is being performed. Data play a secondary or supportive role to the programs that run in each application system. Each application collects and manages its own data.
Advantages
Disadvantages - data redundancy, loss of data integrity
Database Approach (Define here): Facts about events are stored in relational database tables instead of separate files. This improves the efficiency of processing business event data by eliminating data redundancies and improving data integrity. Because the information is stored in relational tables, multiple users can use the information in the way that best suits their needs.
Advantages - integrity of information is better, many of the redundancy problems are solved.
Disadvantages
Distinguish between Logical and Physical Database Models:
Logical modeling - Logical modeling deals with gathering business requirements and converting those requirements into a model. The logical model revolves around the needs of the business, not the database, although the needs of the business are used to establish the needs of the database. Logical modeling involves gathering information about business processes, business entities (categories of data), and organizational units. After this information is gathered, diagrams and reports are produced including entity relationship diagrams, business process diagrams, and eventually process flow diagrams. The diagrams produced should show the processes and data that exists, as well as the relationships between business processes and data. Logical modeling should accurately render a visual representation of the activities and data relevant to a particular business.
Physical modeling - involves the actual design of a database according to the requirements that were established during logical modeling. Logical modeling mainly involves gathering the requirements of the business, with the latter part of logical modeling directed toward the goals and requirements of the database. Physical modeling deals with the conversion of the logical, or business model, into a relational database model. When physical modeling occurs, objects are being defined at the schema level. A schema is a group of related objects in a database. A database design effort is normally associated with one schema.
Relational database model - data are logically organized in two-dimensional tables. Each individual fact or type of information is stored in its own table.
Object-oriented database model - both simple and complex objects can be stored. Include astract data types that allow users to define data to be stored in the database. An object can store attributes and instructions for actions that can be performed on the object or its attributes.
Data Redundancy - a disadvantage of the application approach, explain more fully the problems that can arise because of redundancy. Data Normalization:
1st Normal Form (1NF) - all repeating groups have been eliminated and each row is uniquely identified by a primary key or composite primary key. A repeating group occurs when a row or record contains repeating attributes.
2nd Normal Form (2NF) - a database is in 1st Normal Form and all partial dependencies have been eliminated by creating new tables. A partial dependency occurs when a non-key field is dependent on only a portion of the primary key.
3rd Normal Form (3NF) - a database is in 2nd Normal Form and all transitive dependencies have been eliminated by creating new tables. A transitive dependency occurs when a non-key field depends on another non-key field which depends on the primary key.
Why is data normalization such an important design characteristic of databases?
3rd Normal Form has eliminated the update anomalies associated with the lesser normal forms. Databases that have been normalized to 3rd Normal Form can function properly. The anomalies that normalization reduces or eliminates include:
Updating multiple records during an update
The same item having inconsistent names in different rows
Obstacles to adding new items to the database
The unwanted loss of related data during database deletions
Database Management Systems:
This chapter outlines the differences between applications and database based systems. It discusses basics regarding database structure and design theory.Application based approach to Event Processing (Define Here): Application based approach focuses on the process that is being performed. Data play a secondary or supportive role to the programs that run in each application system. Each application collects and manages its own data.
Database Approach (Define here): Facts about events are stored in relational database tables instead of separate files. This improves the efficiency of processing business event data by eliminating data redundancies and improving data integrity. Because the information is stored in relational tables, multiple users can use the information in the way that best suits their needs.
Distinguish between Logical and Physical Database Models:
Logical modeling - Logical modeling deals with gathering business requirements and converting those requirements into a model. The logical model revolves around the needs of the business, not the database, although the needs of the business are used to establish the needs of the database. Logical modeling involves gathering information about business processes, business entities (categories of data), and organizational units. After this information is gathered, diagrams and reports are produced including entity relationship diagrams, business process diagrams, and eventually process flow diagrams. The diagrams produced should show the processes and data that exists, as well as the relationships between business processes and data. Logical modeling should accurately render a visual representation of the activities and data relevant to a particular business.
Physical modeling - involves the actual design of a database according to the requirements that were established during logical modeling. Logical modeling mainly involves gathering the requirements of the business, with the latter part of logical modeling directed toward the goals and requirements of the database. Physical modeling deals with the conversion of the logical, or business model, into a relational database model. When physical modeling occurs, objects are being defined at the schema level. A schema is a group of related objects in a database. A database design effort is normally associated with one schema.
Relational database model - data are logically organized in two-dimensional tables. Each individual fact or type of information is stored in its own table.
Object-oriented database model - both simple and complex objects can be stored. Include astract data types that allow users to define data to be stored in the database. An object can store attributes and instructions for actions that can be performed on the object or its attributes.
Data Redundancy - a disadvantage of the application approach, explain more fully the problems that can arise because of redundancy.
Data Normalization:
Why is data normalization such an important design characteristic of databases?
3rd Normal Form has eliminated the update anomalies associated with the lesser normal forms. Databases that have been normalized to 3rd Normal Form can function properly. The anomalies that normalization reduces or eliminates include: